Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/10564
DC FieldValueLanguage
dc.contributor.authorHerodotou, Herodotos-
dc.contributor.authorBabu, Shivnath-
dc.contributor.otherΗροδότου, Ηρόδοτος-
dc.date.accessioned2017-12-11T09:41:47Z-
dc.date.available2017-12-11T09:41:47Z-
dc.date.issued2010-
dc.identifier.citationProceedings of the VLDB Endowment VLDB Endowment Hompage archive vol. 3 no. 1-2, September 2010 pp. 1149-1160en_US
dc.identifier.issn2-s2.0-84859229821-
dc.identifier.issnhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84859229821&partnerID=MN8TOARS-
dc.identifier.urihttp://ktisis.cut.ac.cy/handle/10488/10564-
dc.description.abstractThe need to improve a suboptimal execution plan picked by the query optimizer for a repeatedly run SQL query arises routinely. Complex expressions, skewed or correlated data, and changing conditions can cause the optimizer to make mistakes. For example, the optimizer may pick a poor join order, overlook an important index, use a nested-loop join when a hash join would have done better, or cause an expensive, but avoidable, sort to happen. SQL tuning is also needed while tuning multi-tier services to meet service-level objectives. The difficulty of SQL tuning can be lessened considerably if users and higher-level tuning tools can tell the optimizer: "I am not satisfied with the performance of the plan p being used for the query Q that runs repeatedly. Can you generate a (δ%) better plan?" This paper designs, implements, and evaluates Xplus which, to our knowledge, is the first query optimizer to provide this feature. Xplus goes beyond the traditional plan-first-execute-next approach: Xplus runs some (sub)plans proactively, collects monitoring data from the runs, and iterates. A nontrivial challenge is in choosing a small set of plans to run. Xplus guides this process efficiently using an extensible architecture comprising SQL-tuning experts with different goals, and a policy to arbitrate among the experts. We show the effectiveness of Xplus on real-life tuning scenarios created using TPC-H queries on a PostgreSQL database.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherVLDB Endowment-
dc.relation.ispartofProceedings of the VLDB Endowmenten_US
dc.rightsCopyright 2010 VLDB Endowmenten_US
dc.subjectSQLen_US
dc.subjectXplusen_US
dc.titleXplus: A SQL-Tuning-Aware Query Optimizeren_US
dc.typeConference Papersen_US
dc.collaborationDuke Universityen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryUSAen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.14778/1920841.1920984en_US
dc.identifier.scopus2-s2.0-84859229821-
dc.identifier.urlhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84859229821&partnerID=MN8TOARS-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.relation.issue1-
dc.relation.volume3-
cut.common.academicyear2010-2011en_US
item.fulltextNo Fulltext-
item.languageiso639-1other-
item.grantfulltextnone-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-8717-1691-
crisitem.author.parentorgFaculty of Engineering and Technology-
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